Computing method and device based on neural network

Abstract

The embodiment of the invention provides a computing method based on a neural network. The method comprises the steps of receiving an original image; extracting a feature tensor of the original image; and processing the feature tensor based on a trained fixed-point neural network to generate an image thermodynamic diagram. The embodiment of the invention provides the computing method in which the neural network is achieved by a fixed-point method, as fixed-point computation is adopted, a computation amount is small, fewer resources are occupied, and thus requirements on hardware is low.

Description

technical field [0001] The present invention relates to the field of image processing, and more particularly relates to a calculation method and device based on a neural network. Background technique [0002] Neural Networks (NNs), also known as Artificial Neural Networks (ANNs) or Connection Model, is an algorithmic mathematical model that imitates the behavioral characteristics of animal neural networks and performs distributed parallel information processing. Relying on the complexity of the system, the neural network achieves the purpose of processing information by adjusting the interconnection relationship between a large number of internal computing nodes. [0003] Neural networks have been widely and successfully applied in many fields such as speech recognition, text recognition, and image and video recognition. Traditional neural networks use double-precision or single-precision floating-point multiplication / addition calculations as the basic calculation unit. How...

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Problems solved by technology

Traditional neural networks use double-precision or single-precision floating-point multiplication/addition calculations as the basic calculation unit. However, the algorithmic architectur...

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